ICRS_LAB_HAR Dataset

The Human Activity Recognition (HAR) dataset comprises comprehensive data collected from various human activities including walking, running, sitting, standing, and jumping. The dataset is designed to facilitate research in the field of activity recognition using machine learning and deep learning techniques. Each activity is captured through multiple sensors providing detailed temporal and spatial data points, enabling robust analysis and model training.The dataset includes CSV files with annotated activity labels and sensor data, ensuring ease of use for researchers and practitioners. We provide the dataset to authors upon reasonable request to maintain data integrity and confidentiality. This dataset serves as a valuable resource for advancing the development of intelligent systems capable of recognizing and interpreting human activities in real-world scenarios.人类活动识别（Human Activity Recognition，简称HAR）数据集涵盖了从步行、跑步、坐姿、站姿及跳跃等多种人类活动中采集的全面数据。本数据集旨在为采用机器学习与深度学习技术开展活动识别领域的研究提供支持。每项活动均通过多传感器采集，可生成详实的时序与空间数据点，为可靠分析与模型训练提供支撑。数据集包含带有标注活动标签与传感器数据的CSV文件，便于研究人员与从业者使用。为保障数据完整性与机密性，本数据集将在合理申请后向研究者提供。本数据集可为推动可在真实场景中识别与解读人类活动的智能系统发展提供宝贵资源。

搜集汇总

背景与挑战

背景概述

ICRS_LAB_HAR Dataset是一个人类活动识别数据集，专注于采集多种日常活动数据，用于机器学习和深度学习研究。该数据集通过IMU传感器从45名不同年龄和性别的健康受试者采集七种活动数据，采样率为100 Hz，数据以CSV格式提供，并经过预处理和标注，适用于信号处理和可穿戴传感领域的分析。